Uncertainty in Artificial Intelligence
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Belief Revision with Uncertain Inputs in the Possibilistic Setting
Didier Dubois, Henri Prade
This paper discusses belief revision under uncertain inputs in the framework of possibility theory. Revision can be based on two possible definitions of the conditioning operation, one based on min operator which requires a purely ordinal scale only, and another based on product, for which a richer structure is needed, and which is a particular case of Dempster's rule of conditioning. Besides, revision under uncertain inputs can be understood in two different ways depending on whether the input is viewed, or not, as a constraint to enforce. Moreover, it is shown that M.A. Williams' transmutations, originally defined in the setting of Spohn's functions, can be captured in this framework, as well as Boutilier's natural revision.
Keywords: Possibility theory, belief revision, uncertain inputs.
Pages: 236-243
PS Link:
PDF Link: /papers/96/p236-dubois.pdf
AUTHOR = "Didier Dubois and Henri Prade",
TITLE = "Belief Revision with Uncertain Inputs in the Possibilistic Setting",
BOOKTITLE = "Proceedings of the Twelfth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-96)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1996",
PAGES = "236--243"

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